AI/ML Battery Simulation and Design Platform for AvMC Applications

ĀĀĀ The ArmyÆs 2035 goal of conducting multi-domain operations across an array of situations in multiple theaters demands the rapid implementation of new energy technologies.ĀThe National Academies of Sciences concluded that adopting new battery cell technologies must be a key focus in establishing Army dominance: "New battery chemistries offer increased flexibility in the tradeoffs between energy storage, power delivery, rapid charging, and safety. Ongoing S&T studies should be a high priority." Improved battery efficiency is of critical importance to warfighter lethality. Per DEVCOM C5ISR estimates, a 50% increase in battery capacity would translate into more than a 10-pound reduction in soldier load for a 72-hour mission. Army Tactical Power Chiefs worry this problem will compound as the Army continues to add new capabilities that require greater amounts of power and energy.ĀHowever, there are essentially no battery technology research and development software tools to push these future battery solutions forward, compounding the limitations and lack of information on these battery cells. In this Phase II effort, Haylon Technologies will expand on Phase I feasibility study work through a combination of battery cell testing and AI/ML methods to produce a highly-accurate advanced battery pack simulation platform that accelerates the deployment of radically more-efficient Army energy storage solutions,Āwith the goal of estimating battery performance within 85% accuracy, the gold standard for what is possible given inter-cell variability. Haylon will test a range of notable battery cell technologies with a professional R&D facility, employ AI/ML methods to enrich the data, and test the accuracy of battery pack simulations against real-world usage.